An Asymptotic Theory for Estimating Beta-Pricing Models Using Cross-Sectional Regression
Without the assumption of conditional homoskedasticity, a general asymptotic distribution theory for the two-stage cross-sectional regression method shows that the standard errors produced by the Fama-MacBeth procedure do not necessarily overstate the precision of the risk premium estimates. When factors are misspecified, estimators for risk premiums can be biased, and the "t"-value of a premium may converge to infinity in probability even when the true premium is zero. However, when a beta-pricing model is misspecified, the "t"-values for firm characteristics generally converge to infinity in probability, which supports the use of firm characteristics in cross-sectional regressions for detecting model misspecification. Copyright The American Finance Association 1998.
Volume (Year): 53 (1998)
Issue (Month): 4 (08)
|Contact details of provider:|| Web page: http://www.afajof.org/|
More information through EDIRC
|Order Information:||Web: http://www.afajof.org/membership/join.asp|
When requesting a correction, please mention this item's handle: RePEc:bla:jfinan:v:53:y:1998:i:4:p:1285-1309. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If references are entirely missing, you can add them using this form.